1. Field of the Invention
This invention relates to an encoding device for performing an encoding process on digital image information.
2. Description of the Related Art
(Demand for image encoding)
An image has recently been encoded to reduce the capacity of a storage medium or transmission time. The image encoding will hereinafter be used in the same sense as image compression.
In a system wherein an image input device such as a scanner or the like or an image generating device such as a computer or the like and an image output device such as a printer or the like are connected to one another through a network, an input image is compressed, transmitted and stored. Since the image employed in this type of system is high-defined and colored and becomes large in capacity in recent years, an increase in compression rate of the image grows in importance.
Since an image processing device is now making high progress in its resolution and speed, there is a demand for a high-speed encoding processing technique.
(Reversible encoding and non-reversible encoding)
A reversible system and a non-reversible system are known as image encoding systems. In the reversible system, an image (hereinafter called "decoded image") subjected to encoding and decoding processes completely coincides with the original image. In contrast to this, a decoded image employed in the non-reversible system does not completely coincide with the original image and is hence degraded in quality according to its compression rate.
(Problem on non-reversible encoding)
If the image is placed under the same encoding condition in the non-reversible encoding, then the quality (hereinafter called "decoded image quality") of the decoded image is degraded as the compression rate increases. Namely, there is a trade-off between the compression rate and the decoded image quality. This is because the non-reversible encoding achieves a high compression rate by abandoning information in the image, which is considered to be relatively hard to influence vision. Therefore, if the compression rate is low, then information to be abandoned is reduced and the decoded image quality is good. However, if the compression rate is rendered high, then information to be abandoned increases and the decoded image quality is degraded.
It is desirable that both the compression rate and the decoded image quality are normally high upon execution of image compression. It is therefore necessary to provide a mechanism for predicting and controlling the decoded image quality upon the non-reversible encoding.
(Conventional example 1 of the non-reversible encoding system having an image-quality control mechanism)
As an encoding system having an image-quality control mechanism, for example, an "image data encoding device" (Japanese Published Unexamined Patent Application No. Hei 5-292326) is known. Its configuration is shown in FIG. 17. Incidentally, unnecessary parts are omitted. In the drawing, reference numeral 5000 indicates image information, reference numeral 5001 indicates a DCT (Discrete Cosine Transform) part, reference numeral 5002 indicates a linear quantizer, reference numeral 5003 indicates a variable-length encoder, reference numeral 5004 indicates a quantize condition determinator or decider, reference numeral 5005 indicates an image quality determinator, reference numeral 5006 indicates a DCT coefficient or factor, and reference numeral 5007 indicates a quantize DCT coefficient or factor. The input image information 5000 is subjected to DCT by the DCT part 5001 and thereafter quantized by the linear quantizer 5002. The quantized information is subjected to variable-length encoding by the variable-length encoder 5003. At this time, the image quality determinator 5005 performs an image quality decision using an evaluation function, based on the DCT factor 5006 and the quantize DCT factor 5007 and gives instructions for a change of quantize condition to the quantize condition decider 5004 until the value of the evaluation function satisfies a predetermined condition to thereby perform image quality control.
In addition to this, a system for performing image quality control while encoding the entire image under the common quantize conditions through the use of the mean and worst values of evaluation function values in the entire region lying within an image has been described.
The above description shows the conventional or prior art example 1 of the encoding system having the image-quality control mechanism.
(Problem on conventional example 1 of the encoding system having an image-quality control mechanism)
An image-quality degradation principle or norm (image-quality evaluation function) uniform over the entire region in the image is applied to the conventional example 1. However, subjective image quality actually varies even in the case of the same evaluation function values (quantize errors) depending on characteristics of image areas or regions (such as a flat region, a region in which edge images exist in the flat region, a region very complex and including a lot of noise, etc.). Thus, there is a possibility that the image quality will locally fall short of a target or cause waste in terms of the compression rate.
(Conventional example 2 of the non-reversible encoding system having an image-quality control mechanism--characteristic reflection of image areas)
As a method for solving the problem of the aforementioned conventional example 1, for example, an "image data encoding method" (Japanese Published Unexamined Patent Application Hei 6-006610) is known. Its configuration is shown in FIGS. 18 and 19. In the drawing, reference numeral 5100 indicates image information, reference numeral 5101 indicates a DCT part, reference numeral 5102 indicates a linear quantizer, reference numeral 5103 indicates a variable-length encoder, reference numeral 5104 indicates image-quality decision/quantize condition determination unit, reference numeral 5105 indicates a DCT factor, reference numeral 5106 indicates a quantize DCT factor, 5107 indicates coded information, reference numeral 5108 indicates quantize matrix information, reference numeral 5109 indicates decoded image information, reference numeral 5110 indicates a reverse DCT part, reference numeral 5111 indicates a linear reverse quantizer, reference numeral 5112 indicates a subtracter, reference numeral 5113 indicates a vision characteristic weighting part, reference numeral 5114 indicates an image region or area divider, reference numeral 5115 indicates a degradation factor calculator, reference numeral 5116 indicates an objective evaluation scale calculator, and reference numeral 5117 indicates a quantize matrix selection controller.
The conventional example 2 illustrates a system utilizing DCT and quantization in combination as an encoding system. The conventional example 2 is identical to the conventional example 1 in that means for performing switching between quantize characteristics (quantize matrixes) for image-quality control is used. To determine a quantize matrix, the subtracter 5112 extracts an error between the image information 5100 and the decoded image information 5109. The vision characteristic weighting part 5113 assigns weights to the information outputted from the subtracter 5112. The image area divider 5114 divides the input information into areas or regions and the degradation factor calculator 5115 measures various image-quality degradation factors such as block distortion, mosquito noise, etc. The objective evaluation scale calculator 5116 assigns weights to the image-quality degradation factors corresponding to the characteristics of the divided regions or areas to thereby calculate an objective evaluation scale. The quantize matrix selection controller 5117 determines a quantize matrix which satisfies conditions in terms of the amount of codes and the image quality. The conventional example 2 is capable of controlling the image quality with higher accuracy than that obtained in the conventional example 1 in that the local characteristic of the image is reflected upon calculation of the objective evaluation scale.
The above description shows the conventional example 2 of the encoding system having an image-quality control mechanism.
(Problems on conventional examples 1 and 2 of the encoding systems having image-quality control mechanisms)
The conventional examples 1 and 2 do not take into consideration the image output device for outputting the decoded image. However, they are actually different from each other in how to detect image-quality or picture degradation due to encoding depending on the characteristics of the image output device.
Quantization in a space region for reducing the number of bits per pixel, for example, will cause picture degradation due to a gradation level difference called pseudo outline or contour. However, this is deeply concerned with tonal or gradation reproducibility of the output device. Namely, when the output device is poor in tonal reproducibility, the pseudo outline is not judged to be picture degradation due to encoding.
(Proposal of the non-reversible encoding system having an image-quality control mechanism--characteristic reflection of output device)
The present applicant has already proposed a "device for and method of predicting image quality and a device for and method of controlling image quality" (Japanese Patent Application No. Hei 8-229138, unopen to the public) as an approach for solving the problems on the aforementioned conventional examples 1 and 2. Their configurations are shown in FIGS. 20 and 21. In the drawing, reference numeral 5200 indicates image information, reference numeral 5201 indicates a blocking part, reference numeral 5202 indicates a DCT part, reference numeral 5203 indicates a quantizer, reference numeral 5204 indicates an encoding unit, reference numeral 5205 indicates an image information analyzing unit, reference numeral 5206 indicates an image output device characteristic input unit, reference numeral 5207 indicates a quantize selection unit, reference numeral 5208 indicates image analysis information, reference numeral 5209 indicates image output device characteristic information, reference numeral 5210 indicates quantize matrix information, reference numeral 5211 indicates a quantize matrix input part, reference numeral 5212 indicates an image-quality degradation item coding characteristic influence-degree determinator, reference numeral 5213 indicates an image-quality degradation item image characteristic influence-degree determinator, reference numeral 5214 indicates an image-quality degradation item output device characteristic influence-degree determinator, reference numeral 5215 indicates an image-quality degradation item determinator, and reference numeral 5216 indicates a quantize matrix determinator or decider.
Even in the case of the present proposed approach, a system utilizing DCT and quantization in combination is illustrated as an encoding system. The present system is identical to the conventional examples 1 and 2 in that means for performing switching between quantize matrixes is used for image quality control. In order to determine a quantize matrix, the image-quality degradation item coding characteristic influence-degree determinator 5212 of the quantize selection unit 5207 measures the degree of an influence exerted on each image-quality degradation item of the present-selected quantize matrix. The image-quality degradation item image characteristic influence-degree determinator 5213 thereof measures the degree of an influence exerted on each image-quality degradation item of input image information. The image-quality degradation item output device characteristic influence-degree determinator 5214 thereof measures the degree of an influence exerted on each image-quality degradation item of output device characteristic information. Further, the image-quality degradation item determinator 5215 predicts the rate of generation of each image-quality degradation item, based on the above three types of influence degrees. The quantize matrix decider 5216 determines a quantize matrix for achieving target image quality, based on the result of prediction.
The aforementioned proposed approach divides the decoded image quality into a plurality of image-quality degradation items and measures/evaluates the image quality according to the image-quality degradation items The image-quality degradation items may include, for example, a pseudo outline or contour generated due to quantization in a space region to reduce tonal or gradation levels, a blur generated due to the removal of high-frequency components, mosquito noise generated due to quantization in a frequency domain, etc. An advantage is brought about in that the division of the decoded image quality according to the image-quality degradation items in the above-described manner makes it easy to extract one which is high in correlation with image quality corresponding to subjective evaluation from the three characteristics of the input image characteristic, output device characteristic and coding characteristic which have deep connection with the decoded image quality. As a result, high-accuracy image quality control using the above-described characteristic information can be achieved.
(Problems on conventional examples 1 and 2 of the encoding systems having image-quality control mechanisms and the previous proposal)
In the approaches for performing the image-quality control utilizing the analysis information on the divided images as in the prior art 2 and the previous proposal, the accuracy of analysis of the image characteristics exerts a great influence on the accuracy of the image-quality control. This is because the coding characteristic and output device characteristic are often fixed within the system to some extent, whereas the image characteristic is hard to be analyzed with satisfactory accuracy since it is locally changed even within one image.
An the image analysis executed for image-quality control must have high correlation with the result of subjective evaluation. It is desirable in that sense that an analysis size (corresponding to the number of pixels of each divided image) is the extent (corresponding to, e.g., 128 pixels.times.128 lines or the like in the case of an output produced in a resolution of 16 pixels/mm) to which image-quality or picture degradation is detected through the human eyes. However, the image size for sensory evaluation ranges from several tens to hundreds times if one considers that a pixel block size employed in the ordinary or general encoding system is 8 pixels.times.8 lines, thus causing a big problem in terms of pixel implementation.
In the conventional examples, etc., no special mention is not made about component encoding for encoding a color image comprised of a plurality of color components in color component units. A color image processing system for processing a high-resolution image at high speed needs to parallelize processes for respective color components and achieve their speeding-up. In this case, the component encoding is indispensable. When color image information is a natural image such as a photograph and a color space is RGB or YMC, it is generally known that the correlation of image characteristics between respective color components is high. Since the image characteristic used as the image analysis information in the previous proposal is used to represent image contents (patterns) in a region in which gradation varies smoothly, an edge-existing region, etc. while notice is taken of the rate of generation of image-quality degradation items, it can be expected that analysis results, which resemble between the color components in particular, are obtained.
On the other hand, there may be cases in which the degree of an influence on the decoded image quality for each color component is not uniform. This means that there may be cases in which the image quality degradation due to encoding is hard to be detected depending on the color components on an output image represented in colors. Even if such color components are encoded with a compression rate higher than that for other color components, they can be expected to exert no influence on the image quality of the color image.